init

README.md

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----
-license: mit
----
+---
+license: mit
+tags:
+- reinforcement learning
+- world model
+- continuous control
+- robotics
+pipeline_tag: reinforcement-learning
+---
+
+# Dreamer 4 Models for Continuous Control
+
+Checkpoints released as part of an effort to open-source world model research. See [https://github.com/nicklashansen/dreamer4](https://github.com/nicklashansen/dreamer4) for detailed instructions on how to use the released model checkpoints!
+
+
+# Citations
+
+If you find our work useful, please consider citing us as:
+
+```
+@misc{Hansen2026Dreamer4PyTorch,
+    title={Dreamer 4 in PyTorch},
+    author={Nicklas Hansen},
+    year={2026},
+    publisher={GitHub},
+    journal={GitHub repository},
+    howpublished={\url{https://github.com/nicklashansen/dreamer4}},
+}
+```
+
+as well as the original Dreamer 4 paper:
+
+```
+@misc{Hafner2025TrainingAgents,
+    title={Training Agents Inside of Scalable World Models}, 
+    author={Danijar Hafner and Wilson Yan and Timothy Lillicrap},
+    year={2025},
+    eprint={2509.24527},
+    archivePrefix={arXiv},
+    primaryClass={cs.AI},
+    url={https://arxiv.org/abs/2509.24527}, 
+}
+```
+
+## Contact
+
+Correspondence to: [Nicklas Hansen](https://nicklashansen.github.io)

config.json

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+{
+  "name": "Dreamer 4",
+  "format": "torch",
+  "notes": "Model checkpoints for Dreamer 4. See https://github.com/nicklashansen/dreamer4 for details.",
+  "repo_id": "nicklashansen/dreamer4"
+}

dynamics.pt

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tokenizer.pt

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